Skip to main content

AwaDB

AwaDB is an AI Native database for the search and storage of embedding vectors used by LLM Applications.

This notebook explains how to use AwaEmbeddings in LangChain.

# pip install awadb

import the library​

from langchain_community.embeddings import AwaEmbeddings
API Reference:AwaEmbeddings
Embedding = AwaEmbeddings()

Set embedding model

Users can use Embedding.set_model() to specify the embedding model.
The input of this function is a string which represents the model's name.
The list of currently supported models can be obtained here \ \

The default model is all-mpnet-base-v2, it can be used without setting.

text = "our embedding test"

Embedding.set_model("all-mpnet-base-v2")
res_query = Embedding.embed_query("The test information")
res_document = Embedding.embed_documents(["test1", "another test"])

Was this page helpful?


You can also leave detailed feedback on GitHub.